{"id":"W66489813","doi":"10.3182/20100705-3-be-2011.00127","title":"Economic performance assessment with optimized LQG benchmarking in MIMO systems","year":2010,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Benchmarking; Linear-quadratic-Gaussian control; MIMO; Control theory (sociology); Computer science; Control engineering; Engineering; Control (management); Economics; Artificial intelligence; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002471132,0.0002467021,0.0003483775,0.0001809554,0.0000714077,0.0001647592,0.0001944003,0.0001234186,0.00002381138],"category_scores_gemma":[0.000009646784,0.000238959,0.00002953403,0.0001508196,0.00003319157,0.0008362416,0.00002566534,0.0003596735,0.00001811809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002546354,"about_ca_system_score_gemma":0.00003912718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005016712,"about_ca_topic_score_gemma":0.00004990334,"domain_scores_codex":[0.99878,0.0000038676,0.0003833146,0.0002937191,0.0001537929,0.0003853041],"domain_scores_gemma":[0.9995818,0.00002359183,0.0001145143,0.0001310678,0.00006940326,0.00007958843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002682145,0.00001245996,0.07758731,0.0002500308,0.00004009581,0.000001898912,0.0002299737,0.9131506,0.004432429,0.0006725253,0.0001219774,0.003473838],"study_design_scores_gemma":[0.001095194,0.00005032195,0.006467117,0.0001491736,0.00001188017,0.00002493227,0.0001503506,0.9904616,0.0002663826,0.000008803982,0.0009976949,0.0003164859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725809,0.0001125602,0.01213922,0.00002370915,0.0009303751,0.0006544869,0.000003951637,0.0004311526,0.01312369],"genre_scores_gemma":[0.971853,0.00004462424,0.02736676,0.000005565254,0.0002592112,0.0002590222,0.000006433734,0.00006446091,0.0001408862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07731103,"threshold_uncertainty_score":0.9744465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002992269635320411,"score_gpt":0.1939870182283056,"score_spread":0.1909947485929852,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}